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163 results for “Los Angeles”
Inter-Chemical Correlation results for the study: HHEARx2017-1729 (Air Pollution, Placenta Function, and Birth Outcomes in Los Angeles)
Title: Air Pollution, Placenta Function, and Birth Outcomes in Los Angeles <br>Species: Homo sapiens <br>Number of samples: 450 <br>Number of named analytes: 14 <br>Datasource url: https://hheardatacenter.mssm.edu/PublicFile/ViewPublicFile?projectid=48 <br>
Experimental Seismic Data Obtained Using a 3D-Printed Model of the Los Angeles Basin Structure
<p>These data were obtained and analyzed by Park et al., (2022) "Seismic wave simulation using a 3D printed model of the Los Angeles Basin" (doi:10.1038/s41598-022-08732-w).</p> <p> </p>
Site-Specific MCER Response Spectra for Los Angeles Region based on 3-D Numerical Simulations and the NGA West2 Equations
<p><strong>ABSTRACT</strong></p> <p>The Utilization of Ground Motion Simulation (UGMS) committee of the Southern California Earthquake Center (SCEC) developed site-specific, risk-targeted Maximum Considered Earthquake (MCER) response spectra for the Los Angeles region. The long period (T ≥ 2-sec) MCER response spectra were computed as the weighted average of MCER spectral accelerations derived from (1) 3-D numerical ground-motion simulations using the CyberShake computational platform, and (2) empirical ground-motion prediction equations (GMPEs) from the Pacific Earthquake Engineering Research (PEER) Center NGAWest2 project. The short period (T < 2- sec) MCER response spectra were computed exclusively from the NGAWest2 GMPEs. A web-based lookup tool was also developed so users can obtain the MCER response spectrum for a specified latitude and longitude and for a specified site class or 30-m average shear-wave velocity, VS30. The tool provides acceleration ordinates of the MCER response spectrum at 21 natural periods in the 0 to 10-sec band.</p> <p>This dataset includes a Java application to run queries. It serves as the backend data source for the web-based tool that can be found at: <a href="https://data2.scec.org/ugms-mcerGM-tool_v18.4/">https://data2.scec.org/ugms-mcerGM-tool_v18.4/</a>.</p> <p>For more information, please see <a href="https://www.scec.org/research/ugms">https://www.scec.org/research/ugms</a>.</p> <p><strong>DISCLAIMER</strong></p> <p>The UGMS MCER Tool is provided "as is" and without warranties of any kind. While SCEC and the UGMS Committee have made every effort to provide data from reliable sources or methodologies, SCEC and the UGMS Committee do not make any representations or warranties as to the accuracy, completeness, reliability, currency, or quality of any data provided herein. SCEC and the UGMS Committee do not intend the results provided by this tool to replace the sound judgment of a competent professional, who has knowledge and experience in the appropriate field(s) of practice. By using this tool, you accept to release SCEC and the UGMS Committee of any and all liability.</p> <p>Please note: The site-specific, design response spectral acceleration, Sa, returned by this tool for user-specified inputs, must be compared to the minimum Sa requirement described in Section 21.3 of ASCE 7-16 (second and third paragraphs). This minimum Sa is computed as 80% of the design response spectrum derived from the SDS, SD1, and TL values obtained from the ASCE tool at https://asce7hazardtool.online/. The larger of the site-specific Sa and the 80% minimum Sa at each period, T, is the final design response spectral acceleration. This final Sa x 1.5 is the final MCER response spectral acceleration.</p>
Impervious surface and race in Los Angeles County, 2019
This dataset was used to analyze differences in impervious surface levels by race while also accounting for other sociodemographic factors and land use in Los Angeles County. Data was downloaded from the websites of the U.S. Geological Survey, U.S. Census Bureau, and Southern California Association of Governments. Due to redlining and disinvestment in neighborhoods of color, there are generally fewer green spaces and greater urban heat island effects in neighborhoods of color throughout the U.S., as documented in the environmental justice literature. Replacing impervious surfaces like concrete and asphalt with green stormwater infrastructure can help increase green space and reduce urban heat while also meeting local stormwater goals. This research supports existing findings and ties it to the local stormwater context in Los Angeles County. Based on the results of this research, local decision-makers should consider racial demographics when prioritizing where to remove impervious surface and replacing with green stormwater infrastructure.
Figs. 82–84 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 82–84. Abrhexosa ryckmani (Cook), male. 82. Head, lateral view. 83.Thorax, lateral view. 84. Wing.
Figs. 80–81 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 80–81. Abrhexosa grossa (Cook), female terminalia. 80. Segment 7 and terminalia, ventral view. 81. Segment 7 and terminalia, dorsal view.
Figs. 67–70 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 67–70. Quateiella quatei (Cook). 67. Head, lateral view, male. 68.Thorax, lateral view, male. 69. Wing, male. 70. Segments 2–7, ventral view, male.
Figs. 97–98 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 97–98. Abundance of scatopsid species in BioSCAN samples. 97. Quateiella quatei (Cook). 98. Swammerdamella marginata Cook. Red arrows, collecting sites with highest numbers of scatopsids in the samples.
Figs. 47–51 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 47–51. Holoplagia guamensis (Johannsen), male. 47. Head, lateral view. 48.Thorax, lateral view. 49.Wing. 50. Segment 8 and terminalia, ventral view. 51. Segment 8 and terminalia, dorsal view.
Figs. 36–38 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 36–38. Psectrosciara gonzalezae sp.nov. 36.Wing, male holotype. 37.Wing, female paratype 38. Foreleg, female paratype.
Figs. 52–56 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 52–56. Aztecatopse huertai sp.nov., female paratype. 52. Head, lateral view. 53.Thorax, lateral view. 54.Wing. 55.Terminalia, ventral view. 56.Terminalia, dorsal view.
Figs. 31–32 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 31–32. Ectaetia betzi sp.nov, male holotype. 31. Hind femur and tibia. 32. Male terminalia, ventral view.
Figs. 33–35 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 33–35. Psectrosciara gonzalezae sp.nov. 33. Head, lateral view, male holotype. 34. Head, lateral view, female paratype (arrow shows mark of fusion between flagellomeres). 35.Thorax, lateral view, male holotype.
Figs. 95–96 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 95–96. Abundance and species richness of scatopsid species per BioSCAN sampling site. 95. Overall scatopsid abundance per site. 96. Scatopsidae species richness per site. Black arrows, collecting site with no scatopsids in the samples; red arrows, collecting sites with highest numbers of scatopsids in the samples.
Figs. 15–20. Abdomen. 15 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 15–20. Abdomen. 15. Ectaetia betzi sp.nov, male holotype. 16. Psectrosciara gonzalezae sp.nov., female paratype. 17. Scatopse notata (Linnaeus), female. 18. Aztecatopse huertai sp.nov., female paratype. 19. Coboldia fuscipes (Meigen), male. 20. Coboldia fuscipes (Meigen), female (white arrow indicates the diagnostic lunulate sternite 7 posterior incision).
Figs. 11–14. Habitus. 11 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 11–14. Habitus. 11. Abrhexosa grossa (Cook), male. 12. Akorhexosa grossa (Cook), female. 13. 10. Abrhexosa ryckmani (Cook), male. 14. Cooka melanderi (Cook), male.
Figs. 42–44 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 42–44. Scatopse notata (Linnaeus), female. 42. Head, lateral view. 43.Thorax, lateral view. 44.Wing.
Figs. 62–66 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 62–66. Coboldia fuscipes (Meigen). 62. Head, lateral view, female. 63.Thorax, lateral view, female. 64.Wing, female. 65. Segment 7, ventral view, male. 66. Male terminalia, ventral view.
Figs. 89–94 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 89–94. Seasonal abundance of scatopsid species in BioSCAN samples. 89. Psectrosciara gonzalezae, sp.nov. 90. Aztecatopse huertai, sp.nov. 91. Coboldia fuscipes (Meigen). 92. Abrhexosa grossa (Cook). 93. Quateiella quatei (Cook). 94. Swammerdamella marginata Cook.
Figs. 7–10. Habitus. 7 in Urban Scatopsidae (Diptera) of Los Angeles, California, United States
Figs. 7–10. Habitus. 7. Coboldia fuscipes (Meigen), male (black arrow indicates the diagnostic tergite 8 spatulate projection). 8. Coboldia fuscipes (Meigen), female. 9. Quateiella quatei (Cook), male. 10. Quateiella quatei (Cook), female.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.